• Journal of the Semiconductor & Display Technology
• /
• v.20 no.2
• /
• pp.121-125
• /
• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.4
• /
• pp.83-88
• /
• 2021

Cloud services have become the core infrastructure of the digital economy as a basis for collecting, storing, and processing large amounts of data to trigger artificial intelligence-based services and industrial innovation. Recently, cloud services have been spotlighted as a means of responding to corporate crises and changes in the work environment in a national disaster caused by COVID-19. While the cloud is attracting attention, the speed of adoption and diffusion of cloud services is not being actively carried out due to the lack of trust among users and uncertainty about security, performance, and cost. This study compares and analyzes the "Cloud Service Quality and Performance Management System" and the "Cloud Service Certification System" and suggests complementary points and improvement measures for the cloud service quality and performance management system.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.2
• /
• pp.133-137
• /
• 2022

In the smart industry where data plays an important role, cloud computing is being used in a complex and advanced way as a convergence technology because it has and fits well with its strengths. Accordingly, in order to utilize artificial intelligence rather than human beings for quality management of cloud computing services, a consistent standardization method of data collected from various nodes in various areas is required. Therefore, this study analyzed technologies and cases for incorporating artificial intelligence into specific services through previous studies, suggested a plan to use artificial intelligence to comprehensively standardize data in quality management of cloud computing services, and then verified it through case studies. It can also be applied to the artificial intelligence learning model that analyzes the risks arising from the data formalization method presented in this study and predicts the quality risks that are likely to occur. However, there is also a limitation that separate policy development for service quality management needs to be supplemented.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.12
• /
• pp.2294-2314
• /
• 2011

The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

• Journal of Convergence for Information Technology
• /
• v.8 no.6
• /
• pp.173-186
• /
• 2018

While cloud services are expanding, many users are having difficulty in adopting cloud services. This is because there is no information as to which cloud services can be trusted by users. loud service level agreement (Cloud SLA) is an agreement between cloud service providers and cloud service consumers using qualitative and quantitative indicators including quality and performance, etc. of cloud services. In this study, we propose a framework for cloud SLA that can be applied to the domestic cloud industry to improve service levels for cloud service providers and to protect users and also derive the detailed components of cloud SLA applicable to the domestic cloud industry using the proposed framework. Through this result, it is expected that the government will utilize the policy to enhance the reliability between cloud service providers and users under "the Act on the Development of Cloud Computing and Protection of Users", and eventually to activate cloud services by improving the quality and performance level of domestic cloud services and building a user trust.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.6
• /
• pp.383-394
• /
• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.665-666
• /
• 2015

Recently BIM technology has been expanded for using in construction project. However its spread has been delayed than the initial expectations, due to the high-cost of BIM infrastructure development, the lack of regulations, the lack of process and so forth. In construction site phase, especially the analysis of current research trend about IT technologies, virtualization and BIM service, data exchange such as drawing, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. The purpose of this study is enable the cloud computing BIM server to provide several main function such as edit a model, 3D model viewer and checker, mark-up, snapshot in high-performance quality by proper design of VDI system. Concurrent client connection performance is a main technical index of VDI. Through test-bed server client, developed VDI system's multi-connect control will be evaluated. The performance-test result of BIM server VDI will effect to development direction of cloud computing BIM service for commercialization.

• Journal of Information Technology Applications and Management
• /
• v.28 no.2
• /
• pp.1-16
• /
• 2021

In recent years, as IT technologies such as cloud computing and mobile payment have evolved and Internet users have increased, the Internet financial market has become intelligent, mobile, and platformed. This study considers the impact of the psychological characteristics of platform systems and users on the performance of fintech platforms. The results of this study are as follows. Information quality affected trust and commitment, service quality affected commitment only, and system quality affected trust and commitment. The perceived risk affected trust and commitment, and the perceived benefit only affected trust and was shown to have an insignificant relationship with immersion. Trust has been shown to have a significant relationship with commitment, and both trust and commitment affected performance. In the validation of mediation effects, trust has shown a partially mediated effect between information quality, system quality, perceived risks, and perceived benefits and performance. There was no mediation effect between service quality and performance. Immersion has been shown to have a partial mediating effect between information quality, service quality, system quality, perceived risk and performance, and there is no mediating effect between perceived benefits and performance. This study showed what are the main factors that affect the performance of the fintech platform and will be used as a useful foundation for increasing the performance of the platform in the future.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.115-122
• /
• 2021

In the recent past enormous enterprise applications have migrated into the cloud computing (CC). The researchers have contributed to this ever growing technology and as a result several innovations strengthened to offer the quality of service (QoS) as per the demand of the customer. It was treated that management of resources as the major challenge to offer the QoS while focusing on the trade-offs among the performance, availability, reliability and the cost. Apart from these regular key focuses to meet the QoS other key issues in CC are data integrity, privacy, transparency, security and legal aspects (DIPTSL). This paper aims to carry out the literature survey by reflecting on the prior art of the work with regard to QoS in CC and possible implementation of block chain to implement decentralised CC solutions governing DIPTSL as an integral part of QoS.

• International Area Studies Review
• /
• v.21 no.1
• /
• pp.97-117
• /
• 2017

This research highlights the process of adopting cloud computing technology from users' perspective. Concentrating on perceived mechanism from employees side that lead to job performance at work. Cloud computing, the new player in our modern business environment, authors employ diffusion of innovation theory to capture how this new technology affect employees in workplace in terms of job performance. Education for this new system and managerial support by firm were used as moderating variable to test dependent variable, job performance. Research was done through survey from total 284 people working in metropolitan area at South Korea. The result shows that cloud computing system affect positively on work efficiency, and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Group Awareness, 5. Attitude towards New System. To test diffusion factors of cloud computing and job performance, South Korean people actually felt that cloud computing help their job performance and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Attitude towards New System, 5. Group Awareness. As for diffusion factors of cloud computing and productivity, result proved that cloud computing really helps firms, and the extent of diffusion factors that influence from the most to least are as follow: 1. Information Quality, 2. Attitude towards New System, 3. Group Awareness, 4. System Quality, 5. Users' Skill. Two moderating variables, employee education and managerial support were tested to prove whether these two variables affect the job performance and the result displays positive affect for both two factors. To conclude, adopting cloud computing helps firms by increase employees' work efficiency and job performance. In order to accelerate the process employees education really matters because users' skill is the most crucial among diffusion factors.